piv_deform_pass — PIV `estimate` op

• Data kinds: image2d × image2d × flow2d → flow2d

• Call: import pivops; pivops.piv_deform_pass(a, b, flow, info, window=32, overlap=0.5, peak='gauss3', window_func='hann', order=3) (or opspiv.get("piv_deform_pass"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

窓変形つきの 1 段。予測変位で画像そのものを歪めてから相関を取る。

整数ずらし(:func:piv_cross_correlate の `shift`)は、窓の中で変位が

一定という仮定を置く。回転やせん断のように窓の中で変位が変わる場では

相関ピークが潰れるので、2 枚を予測の半分ずつ逆向きに歪めてから相関する

(中央差分の変形)。

Args:

a, b: 画像対。

flow: 予測変位 `(2, h, w)(piv_multipass` などの出力)。

info: その `info`(窓中心の座標が要る)。

window / overlap / peak / window_func: 新しい段の設定。

order: 変形に使う補間の次数(3 = 3 次スプライン)。

Returns:

`(flow (2, h', w'), info)`。返る変位は元の画像座標での総変位。

Detailed usage guide

• piv_displacement family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• (none yet)

Ops the type connects to (they accept `flow2d` as input)

piv_outlier_mask · piv_replace_outliers · piv_vorticity · piv_divergence · piv_flow_magnitude · piv_to_velocity · piv_velocity_gradient · piv_q_criterion

Same category (`estimate`)

piv_cross_correlate · piv_multipass · piv_ensemble_correlate

*Provenance: pivops.py — PIV operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

piv_deform_pass — PIV estimate op